mirror of https://github.com/msberends/AMR.git
225 lines
8.7 KiB
R
Executable File
225 lines
8.7 KiB
R
Executable File
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/freq.R
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\name{freq}
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\alias{freq}
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\alias{frequency_tbl}
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\alias{top_freq}
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\alias{header}
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\alias{print.frequency_tbl}
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\title{Frequency table}
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\usage{
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frequency_tbl(x, ..., sort.count = TRUE,
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nmax = getOption("max.print.freq"), na.rm = TRUE, row.names = TRUE,
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markdown = !interactive(), digits = 2, quote = FALSE,
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header = TRUE, title = NULL, na = "<NA>", droplevels = TRUE,
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sep = " ", decimal.mark = getOption("OutDec"),
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big.mark = ifelse(decimal.mark != ",", ",", "."))
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freq(x, ..., sort.count = TRUE, nmax = getOption("max.print.freq"),
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na.rm = TRUE, row.names = TRUE, markdown = !interactive(),
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digits = 2, quote = FALSE, header = TRUE, title = NULL,
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na = "<NA>", droplevels = TRUE, sep = " ",
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decimal.mark = getOption("OutDec"), big.mark = ifelse(decimal.mark !=
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",", ",", "."))
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top_freq(f, n)
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header(f, property = NULL)
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\method{print}{frequency_tbl}(x, nmax = getOption("max.print.freq",
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default = 15), markdown = !interactive(), header = TRUE,
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decimal.mark = getOption("OutDec"), big.mark = ifelse(decimal.mark !=
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",", ",", "."), ...)
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}
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\arguments{
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\item{x}{vector of any class or a \code{\link{data.frame}}, \code{\link{tibble}} (may contain a grouping variable) or \code{\link{table}}}
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\item{...}{up to nine different columns of \code{x} when \code{x} is a \code{data.frame} or \code{tibble}, to calculate frequencies from - see Examples. Also supports quasiquotion.}
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\item{sort.count}{sort on count, i.e. frequencies. This will be \code{TRUE} at default for everything except when using grouping variables.}
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\item{nmax}{number of row to print. The default, \code{15}, uses \code{\link{getOption}("max.print.freq")}. Use \code{nmax = 0}, \code{nmax = Inf}, \code{nmax = NULL} or \code{nmax = NA} to print all rows.}
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\item{na.rm}{a logical value indicating whether \code{NA} values should be removed from the frequency table. The header (if set) will always print the amount of \code{NA}s.}
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\item{row.names}{a logical value indicating whether row indices should be printed as \code{1:nrow(x)}}
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\item{markdown}{a logical value indicating whether the frequency table should be printed in markdown format. This will print all rows (except when \code{nmax} is defined) and is default behaviour in non-interactive R sessions (like when knitting RMarkdown files).}
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\item{digits}{how many significant digits are to be used for numeric values in the header (not for the items themselves, that depends on \code{\link{getOption}("digits")})}
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\item{quote}{a logical value indicating whether or not strings should be printed with surrounding quotes}
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\item{header}{a logical value indicating whether an informative header should be printed}
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\item{title}{text to show above frequency table, at default to tries to coerce from the variables passed to \code{x}}
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\item{na}{a character string that should be used to show empty (\code{NA}) values (only useful when \code{na.rm = FALSE})}
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\item{droplevels}{a logical value indicating whether in factors empty levels should be dropped}
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\item{sep}{a character string to separate the terms when selecting multiple columns}
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\item{decimal.mark}{%
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used for prettying (longish) numerical and complex sequences.
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Passed to \code{\link{prettyNum}}: that help page explains the details.}
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\item{big.mark}{%
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used for prettying (longish) numerical and complex sequences.
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Passed to \code{\link{prettyNum}}: that help page explains the details.}
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\item{f}{a frequency table}
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\item{n}{number of top \emph{n} items to return, use -n for the bottom \emph{n} items. It will include more than \code{n} rows if there are ties.}
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\item{property}{property in header to return this value directly}
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}
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\value{
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A \code{data.frame} (with an additional class \code{"frequency_tbl"}) with five columns: \code{item}, \code{count}, \code{percent}, \code{cum_count} and \code{cum_percent}.
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}
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\description{
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Create a frequency table of a vector with items or a \code{data.frame}. Supports quasiquotation and markdown for reports. Best practice is: \code{data \%>\% freq(var)}.\cr
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\code{top_freq} can be used to get the top/bottom \emph{n} items of a frequency table, with counts as names.
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}
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\details{
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Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run \code{browseVignettes("AMR")} to read it.
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For numeric values of any class, these additional values will all be calculated with \code{na.rm = TRUE} and shown into the header:
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\itemize{
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\item{Mean, using \code{\link[base]{mean}}}
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\item{Standard Deviation, using \code{\link[stats]{sd}}}
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\item{Coefficient of Variation (CV), the standard deviation divided by the mean}
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\item{Mean Absolute Deviation (MAD), using \code{\link[stats]{mad}}}
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\item{Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using \code{\link[stats]{fivenum}}}
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\item{Interquartile Range (IQR) calculated as \code{Q3 - Q1} using the Tukey Five-Number Summaries, i.e. \strong{not} using the \code{\link[stats]{quantile}} function}
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\item{Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion), calculated as \code{(Q3 - Q1) / (Q3 + Q1)} using the Tukey Five-Number Summaries}
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\item{Outliers (total count and unique count), using \code{\link[grDevices]{boxplot.stats}}}
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}
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For dates and times of any class, these additional values will be calculated with \code{na.rm = TRUE} and shown into the header:
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\itemize{
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\item{Oldest, using \code{\link{min}}}
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\item{Newest, using \code{\link{max}}, with difference between newest and oldest}
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\item{Median, using \code{\link[stats]{median}}, with percentage since oldest}
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}
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In factors, all factor levels that are not existing in the input data will be dropped.
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The function \code{top_freq} uses \code{\link[dplyr]{top_n}} internally and will include more than \code{n} rows if there are ties.
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}
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\section{Read more on our website!}{
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On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
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}
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\examples{
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library(dplyr)
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# this all gives the same result:
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freq(septic_patients$hospital_id)
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freq(septic_patients[, "hospital_id"])
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septic_patients$hospital_id \%>\% freq()
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septic_patients[, "hospital_id"] \%>\% freq()
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septic_patients \%>\% freq("hospital_id")
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septic_patients \%>\% freq(hospital_id) #<- easiest to remember (tidyverse)
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# you could also use `select` or `pull` to get your variables
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septic_patients \%>\%
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filter(hospital_id == "A") \%>\%
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select(mo) \%>\%
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freq()
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# multiple selected variables will be pasted together
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septic_patients \%>\%
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left_join_microorganisms \%>\%
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freq(genus, species)
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# functions as quasiquotation are also supported
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septic_patients \%>\%
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freq(mo_genus(mo), mo_species(mo))
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# group a variable and analyse another
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septic_patients \%>\%
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group_by(hospital_id) \%>\%
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freq(gender)
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# get top 10 bugs of hospital A as a vector
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septic_patients \%>\%
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filter(hospital_id == "A") \%>\%
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freq(mo) \%>\%
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top_freq(10)
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# save frequency table to an object
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years <- septic_patients \%>\%
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mutate(year = format(date, "\%Y")) \%>\%
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freq(year)
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# show only the top 5
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years \%>\% print(nmax = 5)
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# save to an object with formatted percentages
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years <- format(years)
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# print a histogram of numeric values
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septic_patients \%>\%
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freq(age) \%>\%
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hist()
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# or print all points to a regular plot
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septic_patients \%>\%
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freq(age) \%>\%
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plot()
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# transform to a data.frame or tibble
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septic_patients \%>\%
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freq(age) \%>\%
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as.data.frame()
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# or transform (back) to a vector
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septic_patients \%>\%
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freq(age) \%>\%
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as.vector()
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identical(septic_patients \%>\%
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freq(age) \%>\%
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as.vector() \%>\%
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sort(),
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sort(septic_patients$age)) # TRUE
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# it also supports `table` objects
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table(septic_patients$gender,
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septic_patients$age) \%>\%
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freq(sep = " **sep** ")
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# only get selected columns
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septic_patients \%>\%
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freq(hospital_id) \%>\%
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select(item, percent)
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septic_patients \%>\%
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freq(hospital_id) \%>\%
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select(-count, -cum_count)
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# check differences between frequency tables
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diff(freq(septic_patients$trim),
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freq(septic_patients$trsu))
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}
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\keyword{freq}
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\keyword{frequency}
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\keyword{summarise}
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\keyword{summary}
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